Bayesian relative composite quantile regression with ordinal longitudinal data and some case studies-Reference-Cited by-同舟云学术

Bayesian relative composite quantile regression with ordinal longitudinal data and some case studies

Published:2024-03-29 Issue:10 Volume:94 Page:2320-2345
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Tian Yu-Zhu¹²,Wu Chun-Ho³,Tang Man-Lai⁴⁵⁶,Tian Mao-Zai⁷

Affiliation:

1. School of Mathematics and Statistics, Northwest Normal University, Lanzhou, People's Republic of China

2. Gansu Provincial Research Center for Basic Disciplines of Mathematics and Statistics, Lanzhou, People's Republic of China

3. School of Decision Science, The Hang Seng University of Hong Kong, Hong Kong, Hong Kong

4. Centre of Data Innovation Research, University of Hertfordshire, Hatfield, UK

5. Department of Physics, Astronomy & Mathematics, University of Hertfordshire, Hatfield, UK

6. School of Physics, Engineering & Computer Science, University of Hertfordshire, Hatfield, UK

7. School of Statistics, Renmin University of China, Beijing, People's Republic of China

Funder

National Natural Science Foundation of China

Gansu Province of China

Research Matching Grant

FDS Grant

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2024.2335399

Reference45 articles.

1. Wu H, Zhang JT. Nonparametric regression methods for longitudinal data analysis mixed-effects modeling approaches. New York: John Wiley & Sons; 2006.

2. Demidenko E. Mixed models: theory and applications with R. 2nd ed. New York: John Wiley & Sons; 2013.

3. Wang Y, Fu L, Paul S. Analysis of longitudinal data with examples. New York: John Wiley & Sons; 2022.

4. The analysis of longitudinal ordinal data with nonrandom drop-out

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